Call centers are becoming a key channel for managing corporate-to-customer relations. A call center allows for both 24 hours-7 days a week service and support, as well as for selling and marketing of the corporate products. Call centers have become an industry, which relies on hardware (switch boxes, computer-telephone interfaces) as well as software for managing the interactions (Customer Relation Management, CRM). Call centers vary in size, from a single agent, to hundreds of agents. The agents in call centers are trained to handle as many calls as possible, while reflecting during their customer interactions the corporate goals in terms of branding, needs, standards, and customer understanding. Since a call center is often a large operation, with a substantial management chain, sometimes operated by a sub-contractor, modifying the agents' behavior is a complex and sensitive task. Any modification must be carefully analyzed, monitored and approved, before it is deployed by the multitude of agents.
Since the call center should desirably be a profit center, where sales take place, customers are being served, and if possibly retained, therefore, controlling and monitoring the agents' dialogue is of highest importance. The most common tool for this monitoring is either recording the interactions with the customers for later analysis, or allowing the supervisor to tap into the call in real-time. These tools provide limited capabilities and are generally applied for monitoring a single agent conversation. Additional software tools have been built which monitor Key Performance Indicators (KPI) of the entire call center, or of some sub-groups, or even of each individual agent. These indicators are typically used for performing a load balancing and for identifying and resolving operational problems.
In today's rapidly changing markets there is a need for a continuous reevaluation of business strategies and for adjustment of business policies according the market needs, and moreover, for deployment of these adjustments rapidly. Furthermore, the market behavior may be periodic in nature, where the period may vary from days to seasons. Dramatic global events may cause additional market changes, which may reflect at the call-center as different interactions, and different opportunities for the corporate. This sets a need to change rapidly, to adopt to unexpected events, and to do all this in a controlled manner.
Today, these changes are recognized posteriori by deploying an analytic CRM environment or by using data mining tools external to the CRM system. These tools provide analysis of data which has been collected over a long period. The tools typically look for correlations between the various parameters of the call, the agent, the customer and the product, and for patterns of failure or success, and they accordingly offer the call-center management new rules for managing the agents' behavior.
As said, typical call center management systems provide little functionality for continual modification of the agents' behavior. In existing typical systems, business managers (or similar) define business and marketing rules, that are enforced on the corporate agents. For example, the corporate products are priced, offered, and presented to the customers based on said rules. The term “product”, as used herein, refers to any good that the corporate offers, including a service. The business and marketing rules ensure compliance of the corporate agents to the corporate marketing policy and regulations. The rules are used, among others, for guiding the agents, modifying the product presentation when necessary, defining customer eligibility for a certain service or price, and for monitoring the performance of the various agents. Typically, the introduction of a new or modified rule to the various call center agents involves a long cycle of training, acceptance, and application of the rule, a process that may take several months or sometimes even more than a year. One main reason for such a problem is the fact that in traditional CRM systems the rules are hard-coded into the call center software.
A major breakthrough in the design of CRM tools was has occurred by the introduction of the ability to separate the business rules from the software. Instead of being hard-coded into the management environment, the rules are formally stated, and they are compiled or translated into a behavior pattern, affecting the software flow. As a result, a new era of CRM tools has developed—commonly referred to as Analytic CRM. Using Analytic CRM tools the rules are studied, selected, and approved, and then implemented into the next CRM version. This cycle is typically completed twice a year, or in the short case within a magnitude order of months.
This is practically true for any marketing channel, where a long management chain is involved, and multitude of customers interact with the organization's channel. For example, in Web-based services which provide purchasing, support, or information.
The present invention discloses an adaptive fast loop mechanism of performance-monitoring—decision-making and behavior-modification, of agents in a call-center. The adaptive mechanism of the present invention allows for a quick response to the market needs as well as to the call-center performance parameters. The invention can therefore significantly improve all of the KPIs of the call-center.
The following example relates to call center of a bank, and explains problems that arise from the structure of a typical call center. A marketing manager within a corporate defines a business rule, which the corporate agents have to abide to. The rule states as follows:                a. If a cash account owner lives in any of the cities {A, B, or C}; and        b. If the balance of said cash account is above $10,000; and        c. If the cash account owner now wishes to open a saving account; then        d. You may offer the account owner a promotion plan with parameter details {X, Y, Z}.        
At the time of forming the rule relating to this promotional plan, the marketing manager may have had reasons for selecting these specific parameters. Some of the rule parameters may have evolved from pre-conditions that have to be met, for example, state regulations. Other parameters may have resulted from economic considerations. However, what clearly makes one bank more successful than others are those adaptations that are made in order to sell more, and in order to be more attractive to the its customers. In the example above, it may be that residents of a city D are eligible for this plan as well. Further, it may be the case that the regulator requires that the customer balance is above $5,000 in order to be eligible for the promotion plan. It is the bank estimates that caused the rule to include a limit of a $10,000 balance, based on the assumption that this offer will not be attractive to people with less than $10,000 balance.
With respect to the above example, it is desired to provide a mechanism for automatically determining and offering the preference on how to update of the rule, such that: (a) City D is also included in the rule; (b) Cities which are found to be not attractive are removed from the rule; and (c) The exact account balance where it is worth to offer this promotional plan is determined. The result of the desired system might suggest updating the rule as follows:                a. If the account owner lives in any of the cities {A, B, or D} (C was removed, D added); and        b. If the account balance is more than $11,000; and        c. If the owner wishes to open a savings account; then        d. You may offer promotion plan with details {X, Y, R} (Z was replaced by R).        
It is therefore an object of the present invention to provide a call center system having mechanism for analyzing the impacts of application of various call center rules, and for determining optimized parameter values for each of the corporate call center rules.
It is another object of the present invention to provide a mechanism for performing said analysis in a very short cycle.
It is still another object of the present invention to provide a mechanism which performs said analysis automatically.
It is still another object of the present invention to periodically replace rules parameters by the optimized parameter values, as determined by said mechanism.
It is still another object of the present invention to provide constraints for the range of new rule parameters, in order to allow for tight control and conformance with regulations, as determined by said mechanism.
It is still another object of the present invention to provide all of the above for organizations providing service to customers over the web.
Other object and advantages of the present invention will become apparent as the description proceeds.